Observational vs. Experimental Data and How to Control Covariants.

Hello, all. So I have this dataset that contains information pertaining to gun registration in the US including variables such as population, area, urban (I'm guessing that's the number of cities or something), poverty, gun registrations, and homicides. Here is the actual dataset:

So using this data (since it's not a perfectly set environment, it takes a little extra work to find relationships), how would you go about figuring out what factors actually contribute to the number of homicides. I feel a little overwhelmed and after transforming so much data (with basic least squares etc), I'm starting to confuse myself. Can anyone lend me a hand/lead me in the right direction to help me figure out what contributes to homicides?